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EVOLVING NEURO-FUZZY SYSTEM COMBINED LEARNING
2012
Journal:  
Radio Electronics, Computer Science, Control
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Abstract:

Abstract In this work the evolving neuro-fuzzy system with kernel activation function that contains fuzzy support vector machine, normalized radial basis function neural network and general regression neuro-fuzzy network as subsystems is proposed. This network is tuned using both optimization and memory based approaches and does not inclined to the «curse of dimensionality», is able to real time mode information processing by adapting its parameters and structure to problem conditions. Downloads PDF (Українська) Published 2012-07-10 How to Cite Deyneko, A. O., Pliss, I. P., & Bodiansky, Y. V. (2012). EVOLVING NEURO-FUZZY SYSTEM COMBINED LEARNING. Radio Electronics, Computer Science, Control, (1). https://doi.org/10.15588/1607-3274-2012-1-17 More Citation Formats ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX Issue No. 1 (2012): Radio Electronics, Computer Science, Control Section Neuroinformatics and intelligent systems License Copyright (c) 2014 A. O. Deyneko, I. P. Pliss, Y. V. Bodiansky

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Radio Electronics, Computer Science, Control

Journal Type :   Uluslararası

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Radio Electronics, Computer Science, Control